Geometric hashing (GH) and partial pose clustering are well-known algorithms for pattern recognition. However, the performance of both these algorithms degrades rapidly with an increase in scene clutter and the measurement uncertainty in the detected features. The primary contribution of this paper
3D object pose form clustering with multiple views
β Scribed by George Stockman; Juan Carlos Esteva
- Publisher
- Elsevier Science
- Year
- 1985
- Tongue
- English
- Weight
- 369 KB
- Volume
- 3
- Category
- Article
- ISSN
- 0167-8655
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
We present a method for planning sequences of views for recognition and pose (orientation) determination of 3-D objects of arbitrary shape. The approach consists of a learning stage in which we derive a recognition and pose identification plan and a stage in which actual recognition and pose identif
This paper addresses the problem of recognizing 3D objects from 2D intensity images. It describes the object recognition system named RIO (relational indexing of objects), which contains a number of new techniques. RIO begins with an edge image obtained from a pair of intensity images taken with a s
A new approach to 3D object recognition using multiple 2D camera views is proposed. The recognition system includes a turntable, a top camera, and a lateral camera. Objects are placed on the turntable for translation and rotation in the recognition process. 3D object recognition is accomplished by m
This paper presents an algorithm for generating the Medial Axis Transform (MAT) of 3D objects with free form boundaries that are obtained by extrusion along a line or revolution about an axis. The algorithm proposed uses the exact representation of the part and generates an approximate rational spli